Carnegie Mellon University
Browse

Building Process Improvement Business Cases Using Bayesian Belief Networks and Monte Carlo Simulation

Download (622.44 kB)
report
posted on 2009-07-01, 00:00 authored by Ben Linders
Many organizations require quality improvement initiatives to be based on quantified business cases. This leads some organizations to start measurement programs to collect data about current performance-a lengthy and expensive process that requires a strong commitment from management. This report describes a collaboration between the Software Engineering Institute and Ericsson Research and Development, The Netherlands, to build a business case using high maturity measurement approaches that require limited measurement effort. For this project, a Bayesian belief network (BBN) and Monte Carlo simulation were combined to build a business case for quality improvement. Using a BBN provided quick insight into potential areas of improvement based on relevant quality factors and the current performance level of the organization. Monte Carlo simulation enabled a detailed calculation of the likely business results in the areas of potential improvement. This approach led to a decision to implement agile methods to improve the quality of requirements.

History

Date

2009-07-01

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC